Book Image

DevOps Adoption Strategies: Principles, Processes, Tools, and Trends

Book Image

DevOps Adoption Strategies: Principles, Processes, Tools, and Trends

Overview of this book

DevOps is a set of best practices enabling operations and development teams to work together to produce higher-quality work and, among other things, quicker releases. This book helps you to understand the fundamentals needed to get started with DevOps, and prepares you to start deploying technical tools confidently. You will start by learning the key steps for implementing successful DevOps transformations. The book will help you to understand how aspects of culture, people, and process are all connected, and that without any one of these elements DevOps is unlikely to be successful. As you make progress, you will discover how to measure and quantify the success of DevOps in your organization, along with exploring the pros and cons of the main tooling involved in DevOps. In the concluding chapters, you will learn about the latest trends in DevOps and find out how the tooling changes when you work with these specialties. By the end of this DevOps book, you will have gained a clear understanding of the connection between culture, people, and processes within DevOps, and learned why all three are critically important.
Table of Contents (18 chapters)
1
Section 1: Principles of DevOps and Agile
5
Section 2: Developing and Building a Successful DevOps Culture
8
Section 3: Driving Change and Maturing Your Processes
12
Section 4: Implementing and Deploying DevOps Tools

Understanding the DataOps ecosystem

One of the most common misconceptions around DataOps is that under the covers, it is just DevOps applied to data analytics. While the name shares similarities with both DevOps and DataOps, they're not the same.

Look at the following diagram, which depicts the DevOps loop:

Figure 11.1 – Graphic showing the phases of DevOps in an infinite loop

DevOps is often depicted as an infinite loop. As you can see in the previous diagram, DataOps is different. When illustrating DataOps, it is shown as an intersection of value and innovation pipelines, as you can see in the following diagram:

Figure 11.2 – DataOps depiction showing a value pipeline along the top and innovation from bottom to top

DataOps communicates that data analytics can achieve what DevOps accomplished for software development. That is, when data teams use new tools and methodologies, DataOps can result in an order of magnitude...